ct_selection_untitled-8F5A2CFF.R

gg <- cces %>% 
  filter(year >= 2022) %>% 
  cces_id5(ideo5) %>% 
  cces_attend(pew_attendance) %>% 
  group_by(att) %>% 
  ct(id5, wt = weight, show_na = FALSE) %>% filter(att != "NA")


gg %>% 
  mutate(lab = round(pct, 2)) %>% 
  ggplot(., aes(x = 1, y = pct, fill =id5)) +
  geom_col(color = "black") + 
  coord_flip() +
  facet_wrap(~ att, ncol =1, strip.position = "left") +
  theme_rb() +
  scale_fill_manual(values = c("#2166AC", "#67A9CF", "azure4", "#EF8A62","#B2182B")) +
  theme(legend.position = "bottom") +
  scale_y_continuous(labels = percent) +
  theme(strip.text.y.left = element_text(angle=0)) +
  guides(fill = guide_legend(reverse=T, nrow = 1)) +
  theme(axis.title.y=element_blank(), axis.text.y=element_blank(), axis.ticks.y=element_blank()) +
  theme(panel.grid.minor.y=element_blank(), panel.grid.major.y=element_blank()) +
  geom_text(aes(label = ifelse(pct >.06, paste0(lab*100, '%'), '')), position = position_stack(vjust = 0.5), size = 10, family = "font", color = "black") +
  geom_text(aes(label = ifelse(id5 == "Very Conservative", paste0(lab*100, '%'), '')), position = position_stack(vjust = 0.5), size = 10, family = "font", color = "white") +
  geom_text(aes(label = ifelse(id5 == "Very Liberal" & pct > .06, paste0(lab*100, '%'), '')), position = position_stack(vjust = 0.5), size = 10, family = "font", color = "white") +
  theme(plot.title = element_text(size = 16)) +
  theme(strip.text.y.left = element_text(angle = 0, hjust = 1)) +
  labs(x = "", y = "", title = "Religious Attendance and Political Ideology", caption = "@ryanburge\nData: Cooperative Election Study, 2022-2023") 
save("att_id52023.png", wd = 9, ht = 5)

gg <- cces %>% 
  filter(year >= 2022) %>% 
  cces_race(race) %>%  
  cces_attend(pew_attendance) %>% 
  mutate(lib = case_when(ideo5 == 1 | ideo5 == 2 ~ 1, 
                         ideo5 <= 5 ~ 0)) %>% 
  group_by(att, race) %>% 
  mean_ci(lib, wt = weight, ci = .84) %>% filter(att != "NA")

gg %>% 
  mutate(lab = round(mean, 2)) %>% 
  ggplot(., aes(x = att, y = mean, fill = race)) +
  geom_col(color = "black", position = "dodge") +
  facet_wrap(~ race) +
  scale_fill_manual(values = c(moma.colors("ustwo", 5))) +
  theme_rb() +
  y_pct() + 
  error_bar() +
  theme(axis.text.x = element_text(size = 10)) +
  lab_bar(top = FALSE, type = lab, pos = .04, sz = 5.5) +
  theme(strip.text = element_text(size = 20)) +
  labs(x = "", y = "", title = "Share Who Identify as Liberal by Race and Religious Attendance", caption = "@ryanburge\nData: Cooperative Election Study, 2022-2023")
save("liberal_race_attend.png")


gg <- cces %>% 
  filter(year >= 2022) %>% 
  mutate(trad = frcode(baptist == 1 ~ "Southern Baptist",
                       baptist == 2 ~ "ABCUSA",
                       baptist == 3 ~ "Natl. Baptist Convention",
                       baptist == 4 ~ "Progressive Baptist Convention",
                       baptist == 5 ~ "Independent Baptist",
                       baptist == 6 ~ "Baptist General Conference",
                       baptist == 7 ~ "Baptist Miss. Association",
                       baptist == 8 ~ "Conservative Bapt. Association", 
                       baptist == 9 ~ "Free Will Baptist",
                       baptist == 10 ~ "Gen. Assoc. of Reg. Bapt.",
                       baptist == 90 ~ "Other Baptist",
                       methodist == 1 ~ "United Methodist",
                       methodist == 2 ~ "Free Methodist",
                       methodist == 3 ~ "African Methodist Episcopal",
                       methodist == 4 ~ "AME - Zion",
                       methodist == 5 ~ "Christian Methodist Episcopal",
                       methodist == 90 ~ "Other Methodist",
                       nondenom == 1 ~ "Nondenom Evangelical",
                       nondenom == 2 ~ "Nondenom Fundamentalist",
                       nondenom == 3 ~ "Nondenom Charismatic",
                       nondenom == 4 ~ "Interdenominational",
                       nondenom == 5 ~ "Community Church",
                       nondenom == 90 ~ "Other Nondenom",
                       lutheran == 1 ~ "ELCA",
                       lutheran == 2 ~ "Lutheran - Missouri Synod",
                       lutheran == 3 ~ "Lutheran - Wisconsin Synod",
                       lutheran == 4 ~ "Other Lutheran",
                       presbyterian == 1 ~ "PCUSA",
                       presbyterian == 2 ~ "PCA",
                       presbyterian == 3 ~ "Associated Reformed Presbyterian",
                       presbyterian == 4 ~ "Cumberland Presbyterian", 
                       presbyterian == 5 ~ "Orthodox Presbyterian",
                       presbyterian == 6 ~ "Evangelical Presbyterian",
                       presbyterian == 90 ~ "Other Presbyterian",
                       pentecostal == 1 ~ "Assemblies of God",
                       pentecostal == 2 ~ "Church of God Cleveland TN",
                       pentecostal == 3 ~ "Four Square Gospel", 
                       pentecostal == 4 ~ "Pentecostal Church of God",
                       pentecostal == 5 ~ "Pentecostal Holiness Church",
                       pentecostal == 6 ~ "Church of God in Christ",
                       pentecostal == 7 ~ "Church of God of the Apostolic Faith",
                       pentecostal == 8 ~ "Assembly of Christian Churches",
                       pentecostal == 9 ~ "Apostolic Christian",
                       pentecostal == 90 ~ "Other Pentecostal",
                       episcopal == 1 ~ "ECUSA",
                       episcopal == 2 ~ "Church of England",
                       episcopal == 3 ~ "Anglican Orthodox",
                       episcopal == 4 ~ "Reformed Episcopal",
                       episcopal == 90 ~ "Other Episcopal",
                       christian == 1 ~ "Church of Christ",
                       christian == 2 ~ "Disciples of Christ",
                       christian == 3 ~ "Christian Church",
                       christian == 90 ~ "Other Christian Church",
                       congregational == 1 ~ "United Church of Christ",
                       congregational == 2 ~ "Conservative Cong. Christian",
                       congregational == 3 ~ "National Assoc. of Cons. Cong.",
                       congregational == 90 ~ "Other Cong.",
                       holiness == 1 ~ "Church of the Nazarene",
                       holiness == 2 ~ "Wesleyan Church",
                       holiness == 4 ~ "Christian and Missionary Alliance",
                       holiness == 5 ~ "Church of God",
                       holiness == 6 ~ "Salvation Army",
                       reformed == 1 ~ "Reformed Church in America",
                       reformed == 2 ~ "Christian Reformed",
                       reformed == 90 ~ "Other Reformed",
                       adventist == 1 ~ "Seventh Day Adventist")) %>%
  cces_attend(pew_attendance) %>% 
  mutate(lib = case_when(ideo5 == 1 | ideo5 == 2 ~ 1, 
                         ideo5 <= 5 ~ 0)) %>% 
  group_by(trad, att) %>% 
  mean_ci(lib, wt = weight, ci = .84) %>% 
  filter(att != "NA")


gg1 <- gg %>% 
  group_by(trad) %>% 
  summarise(sum = sum(n)) 

both <- left_join(gg, gg1) %>% filter(trad != "NA")

both <- both %>% 
  filter(sum > 450)

both %>% 
  ggplot(., aes(x = att, y = mean, fill = trad, group = trad)) +
  geom_col(color = "black") +
  facet_wrap(~ trad) +
  theme_rb() +
  y_pct() +
  scale_fill_manual(values = c(moma.colors("Panton", 20))) +
  scale_x_discrete(breaks = function(x) x[c(TRUE, FALSE)])  +
  geom_smooth(se = FALSE, method = lm, color = "black", linetype = "twodash") +
  labs(x = "Attendance", y = "", title = "Share Who Identify as Liberal by Church Attendance", subtitle = "Among the 20 Largest Protestant Denominations", 
       caption = "@ryanburge\nData: Cooperative Election Study, 2022-2023")
save("att_liberal_top20.png", ht = 11)


gg <- cces %>% 
  filter(year >= 2020) %>% 
  mutate(rel = frcode(religion == 2 ~ "Catholic", 
                      religion == 3 ~ "LDS", 
                      religion == 5 ~ "Jewish", 
                      religion == 6 ~ "Muslim", 
                      religion == 7 ~ "Buddhist", 
                      religion == 8 ~ "Hindu")) %>% 
  cces_attend(pew_attendance) %>% 
  group_by(rel, att) %>% 
  mutate(lib = case_when(ideo5 == 1 | ideo5 == 2 ~ 1, 
                         ideo5 <= 5 ~ 0)) %>% 
  mean_ci(lib, wt = weight, ci = .84) %>% 
  filter(att != "NA") %>% 
  filter(rel != "NA")



gg %>% 
  mutate(lab = round(mean, 2)) %>% 
  ggplot(., aes(x = att, y = mean, fill = rel)) +
  geom_col(color = "black", position = "dodge") +
  facet_wrap(~ rel) +
  scale_fill_manual(values = c(moma.colors("Connors", 6))) +
  theme_rb() +
  y_pct() + 
  error_bar() +
  theme(axis.text.x = element_text(size = 10)) +
  lab_bar(top = FALSE, type = lab, pos = .04, sz = 5.5) +
  theme(strip.text = element_text(size = 20)) +
  labs(x = "", y = "", title = "Share Who Identify as Liberal by Religious Attendance", caption = "@ryanburge\nData: Cooperative Election Study, 2020-2023")
save("liberal_non_protestant_attend.png", ht = 8)